Course Synopsis

The focus of this course is financial econometrics. This differs from a typical introductory econometrics course in that the motivating examples will all come from finance. The course will cover much more on time-series econometrics than a typical econometrics course, and therefore less on other traditional subjects. Sub-themes will be on computational methods, and connections to other areas of statistical practice such as data science and machine learning.

The course is very applied in nature. That means that I will focus more on models, methods and implementation than on formal proofs. We will use the EViews programs that accompany the main textbook as well as do some programming in the Python programming language.

Prerequisites

• Statistics 2000/2300 Business Statistics
• Math 1100 or 1210 Calculus
• Or approval of the professor

Students must be prepared to program in Python for computational assignments. No prior programming experience is required!

Instructor

Tyler Brough, PhD, Associate Professor of Finance

Eccles Business Building 605

Slack

All class communication will take place using Slack, a messaging system that replaces email. Students will be invited to the Econ 5330 Slack channel prior to the first week of class.

Clients for most computing and mobile platforms can be downloaded from the Slack website, or students may use the web client via a desktop browser.